CN113324541A - Positioning method and device and positioning system - Google Patents
Positioning method and device and positioning system Download PDFInfo
- Publication number
- CN113324541A CN113324541A CN202110611125.8A CN202110611125A CN113324541A CN 113324541 A CN113324541 A CN 113324541A CN 202110611125 A CN202110611125 A CN 202110611125A CN 113324541 A CN113324541 A CN 113324541A
- Authority
- CN
- China
- Prior art keywords
- target object
- imu
- measurement data
- data
- sensors
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Granted
Links
- 238000000034 method Methods 0.000 title claims abstract description 56
- 238000005259 measurement Methods 0.000 claims abstract description 169
- 230000001133 acceleration Effects 0.000 claims description 69
- 239000011159 matrix material Substances 0.000 claims description 40
- 238000006243 chemical reaction Methods 0.000 claims description 16
- 230000004927 fusion Effects 0.000 claims description 12
- 230000009466 transformation Effects 0.000 claims description 9
- 238000005516 engineering process Methods 0.000 abstract description 11
- 230000002159 abnormal effect Effects 0.000 description 10
- 230000008878 coupling Effects 0.000 description 8
- 238000010168 coupling process Methods 0.000 description 8
- 238000005859 coupling reaction Methods 0.000 description 8
- 238000010586 diagram Methods 0.000 description 4
- 230000000694 effects Effects 0.000 description 4
- 238000001914 filtration Methods 0.000 description 3
- 238000012545 processing Methods 0.000 description 3
- 238000012795 verification Methods 0.000 description 3
- 238000004891 communication Methods 0.000 description 2
- 238000010276 construction Methods 0.000 description 2
- 238000005034 decoration Methods 0.000 description 2
- 230000002950 deficient Effects 0.000 description 2
- 238000012986 modification Methods 0.000 description 2
- 230000004048 modification Effects 0.000 description 2
- 238000005457 optimization Methods 0.000 description 2
- 238000006073 displacement reaction Methods 0.000 description 1
- 238000009434 installation Methods 0.000 description 1
- 230000010354 integration Effects 0.000 description 1
- 230000003287 optical effect Effects 0.000 description 1
- 239000002904 solvent Substances 0.000 description 1
- 238000012360 testing method Methods 0.000 description 1
- 230000001960 triggered effect Effects 0.000 description 1
Images
Classifications
-
- G—PHYSICS
- G01—MEASURING; TESTING
- G01C—MEASURING DISTANCES, LEVELS OR BEARINGS; SURVEYING; NAVIGATION; GYROSCOPIC INSTRUMENTS; PHOTOGRAMMETRY OR VIDEOGRAMMETRY
- G01C21/00—Navigation; Navigational instruments not provided for in groups G01C1/00 - G01C19/00
- G01C21/10—Navigation; Navigational instruments not provided for in groups G01C1/00 - G01C19/00 by using measurements of speed or acceleration
- G01C21/12—Navigation; Navigational instruments not provided for in groups G01C1/00 - G01C19/00 by using measurements of speed or acceleration executed aboard the object being navigated; Dead reckoning
- G01C21/16—Navigation; Navigational instruments not provided for in groups G01C1/00 - G01C19/00 by using measurements of speed or acceleration executed aboard the object being navigated; Dead reckoning by integrating acceleration or speed, i.e. inertial navigation
- G01C21/165—Navigation; Navigational instruments not provided for in groups G01C1/00 - G01C19/00 by using measurements of speed or acceleration executed aboard the object being navigated; Dead reckoning by integrating acceleration or speed, i.e. inertial navigation combined with non-inertial navigation instruments
-
- G—PHYSICS
- G01—MEASURING; TESTING
- G01C—MEASURING DISTANCES, LEVELS OR BEARINGS; SURVEYING; NAVIGATION; GYROSCOPIC INSTRUMENTS; PHOTOGRAMMETRY OR VIDEOGRAMMETRY
- G01C21/00—Navigation; Navigational instruments not provided for in groups G01C1/00 - G01C19/00
- G01C21/20—Instruments for performing navigational calculations
Landscapes
- Engineering & Computer Science (AREA)
- Radar, Positioning & Navigation (AREA)
- Remote Sensing (AREA)
- Automation & Control Theory (AREA)
- Physics & Mathematics (AREA)
- General Physics & Mathematics (AREA)
- Navigation (AREA)
Abstract
The invention discloses a positioning method, a positioning device and a positioning system. Wherein, the method comprises the following steps: fusing first measurement data of a target object to obtain speed data of the target object, wherein the first measurement data are motion data of the target object, which are acquired by at least two inertial sensors IMU; acquiring second measurement data of the target object, wherein the second measurement data is motion data of the target object acquired by other sensors except at least two IMU sensors in the positioning system; and fusing the speed data and the second measurement data to obtain the current attitude of the target object. The invention solves the technical problems that in the scheme of positioning by using the IMU in the related technology, the working state of the IMU device can not be effectively detected and fed back, when the IMU device fails, the IMU device can not be found in time, and potential safety hazards exist when the IMU device is still positioned by using data acquired by the IMU.
Description
Technical Field
The invention relates to the technical field of positioning, in particular to a positioning method, a positioning device and a positioning system.
Background
Positioning technology is widely applied in various fields, for example, autopilot, logistics robot, dining robot, unmanned aerial vehicle, and the like. An Inertial Measurement Unit (IMU) can provide high-frequency, continuous, full-dimensional motion information, and is the most commonly used sensor in positioning. The existing positioning technology generally integrates IMU data to obtain a prediction result of a relative attitude.
Fig. 1 is a flow chart of positioning based on an IMU according to the prior art, as shown in fig. 1, the IMU is used as a core sensor for predicting attitude, and other sensors are used as assistance for acquiring attitude observation values, and these sensors mainly include Wheel encoders (Wheel encoders), Global Navigation Satellite System (GNSS), three-dimensional laser radar (lidar), and High definition Map (High definition Map). The IMU can integrate the acceleration and the angular velocity to obtain a relative attitude prediction result, other sensors can obtain an attitude observation result, and then the relative attitude prediction result obtained by the IMU and the attitude observation results obtained by the other sensors can be fused to obtain the attitude at the current moment. As can be seen from fig. 1, the IMU can provide vital acceleration and angular velocity measurements for positioning, and by integrating the acceleration and angular velocity, important relative displacement and relative rotation values can be obtained. The existing positioning technical scheme is divided into a tight coupling direction and a loose coupling direction according to the difference of the coupling modes of the fusion part. The close coupling mode mainly adopts an optimization idea, and each sensor provides a constraint mode to construct an optimization problem and optimize a positioning result. The loose coupling mode mainly uses the filtering thought, each sensor calculates a positioning result by using own data, and then a plurality of positioning results are fused in a certain mode to obtain the positioning result at the current moment. The scheme of filtering is represented by kalman filtering. The IMU, whether optimized or filtered, is the most commonly used sensor in positioning systems due to its property of providing high frequency, continuous, full-dimensional motion information.
However, the above technical solutions cannot effectively detect and feed back the operating state of the IMU device; the IMU belongs to a high-precision sensor, and is easy to be influenced by factors such as extreme temperature (high temperature or low temperature), severe vibration, collision and the like after long-time work, so that an IMU device is damaged irreversibly. Particularly, in the automatic driving technology, the IMU needs to work for a long time, and the situations of sudden braking, severe vibration and even collision exist, so that the IMU device is a great test. If the positioning system cannot find IMU with abnormal data in time, the positioning system continues to use wrong IMU data to predict the attitude, and finally the positioning can be converged to a very poor result, and a great deviation is generated between the positioning system and the real attitude. This is unacceptable for many products with positioning technology, which may carry an unpredictable risk.
Aiming at the problems that in the scheme of positioning by using the IMU in the related technology, the working state of an IMU device cannot be effectively detected and fed back, when the IMU device fails, the IMU device cannot be found in time, and potential safety hazards exist when the IMU device is still used for positioning, an effective solution is not provided at present.
Disclosure of Invention
The embodiment of the invention provides a positioning method, a positioning device and a positioning system, which are used for at least solving the technical problems that in a scheme of positioning by using an IMU in the related technology, the working state of an IMU device cannot be effectively detected and fed back, when the IMU device fails, the IMU device cannot be found in time, and potential safety hazards exist when the IMU device is still positioned by using data acquired by the IMU.
According to an aspect of an embodiment of the present invention, there is provided a positioning method, including: fusing first measurement data of a target object to obtain speed data of the target object, wherein the first measurement data are motion data of the target object, acquired by at least two inertial sensors IMUs; acquiring second measurement data of the target object, wherein the second measurement data is the motion data of the target object acquired by other sensors in the positioning system except the at least two IMU sensors; and fusing the speed data and the second measurement data to obtain the current posture of the target object.
Optionally, before the fusing the first measurement data of the target object to obtain the speed data of the target object, the positioning method further includes: acquiring first measurement data of the target object; acquiring a data identifier of the first measurement data; determining a total number of IMU sensors in the positioning system that are operating properly based on the data identification; and generating alarm information under the condition that the total number is less than a preset value.
Optionally, fusing the first measurement data of the target object to obtain the speed data of the target object, including: converting first measurement data acquired by a secondary IMU sensor of the at least two IMU sensors into a main coordinate system corresponding to a main IMU sensor of the at least two IMU sensors; and obtaining the speed data based on the measurement data, the weighting matrix and the conversion matrix in the main coordinate system.
Optionally, when the speed data is an X-axis acceleration of the target object in the main coordinate system, obtaining the speed data based on the measurement data, the weighting matrix, and the transformation matrix in the main coordinate system includes: determining the X-axis acceleration of the target object in the main coordinate system through a first formula, wherein the first formula is as follows: and y is Hx, wherein y represents the X-axis acceleration measured value of the target object in the main coordinate system, H represents the conversion matrix, and X represents the X-axis acceleration of the target object in the main coordinate system.
Optionally, obtaining the speed data based on the measurement data, the weighting matrix, and the transformation matrix in the main coordinate system includes: determining the X-axis acceleration of the target object in the main coordinate system through a second formula, wherein the second formula is as follows:
where x is ax and W represents the weighting matrix.
Optionally, the weighting matrix is determined according to a standard deviation of the acceleration noise on the X-axis coordinate in the main coordinate system.
Optionally, after the first measurement data of the target object is fused to obtain the speed data of the target object, the positioning method further includes: and updating the standard deviation of the acceleration noise.
Optionally, the positioning method further includes: converting first measurement data acquired by a secondary IMU sensor of the at least two IMU sensors into a main coordinate system corresponding to a main IMU sensor of the at least two IMU sensors; constructing a measurement value equation and a parity equation based on the measurement data in the coordinate system; generating a parity table based on the measurement equation and the parity equation, wherein the parity table is used to represent the number of IMU sensors in the positioning system that have failed.
Optionally, fusing the speed data and the second measurement data to obtain the current posture of the target object, including: determining a relative pose prediction result of the target object based on the velocity data; determining a pose observation of the target object based on the second measurement data; and fusing the relative attitude prediction result and the attitude observation result to obtain the current attitude of the target object.
According to another aspect of the embodiments of the present invention, there is also provided a positioning apparatus, including: the system comprises a first acquisition unit, a second acquisition unit and a third acquisition unit, wherein the first acquisition unit is used for fusing first measurement data of a target object to obtain speed data of the target object, and the first measurement data are motion data of the target object acquired by at least two inertial sensors IMU; a second obtaining unit, configured to obtain second measurement data of the target object, where the second measurement data is motion data of the target object acquired by a sensor other than the at least two IMU sensors in the positioning system; and the third acquisition unit is used for fusing the speed data and the second measurement data to obtain the current posture of the target object.
Optionally, the positioning device further comprises: the fourth acquisition unit is used for acquiring the first measurement data of the target object before the first measurement data of the target object is fused to obtain the speed data of the target object; a fifth obtaining unit, configured to obtain a data identifier of the first measurement data; a determination unit for determining the total number of IMU sensors in the positioning system that are operating normally based on the data identity; and the generating unit is used for generating alarm information under the condition that the total number is less than a preset value.
Optionally, the first obtaining unit includes: the conversion module is used for converting first measurement data acquired by a secondary IMU sensor in the at least two IMU sensors into a main coordinate system corresponding to a main IMU sensor in the at least two IMU sensors; and the first acquisition module is used for acquiring the speed data based on the measurement data, the weighting matrix and the conversion matrix in the main coordinate system.
Optionally, when the speed data is an X-axis acceleration of the target object in the main coordinate system, the obtaining module includes: a first determining module, configured to determine an X-axis acceleration of the target object in the main coordinate system according to a first formula, where the first formula is: and y is Hx, wherein y represents the X-axis acceleration measured value of the target object in the main coordinate system, H represents the conversion matrix, and X represents the X-axis acceleration of the target object in the main coordinate system.
Optionally, the obtaining module includes: a second determining module, configured to determine an X-axis acceleration of the target object in the main coordinate system according to a second formula, where the second formula is:
where x is ax and W represents the weighting matrix.
Optionally, the weighting matrix is determined according to a standard deviation of the acceleration noise on the X-axis coordinate in the main coordinate system.
Optionally, the positioning device further comprises: and the updating unit is used for updating the standard deviation of the acceleration noise after the first measurement data of the target object are fused to obtain the speed data of the target object.
Optionally, the positioning device further comprises: the conversion unit is used for converting first measurement data acquired by a secondary IMU sensor in the at least two IMU sensors into a main coordinate system corresponding to a main IMU sensor in the at least two IMU sensors; a construction unit for constructing a measurement value equation and a parity equation based on the measurement data in the coordinate system; a generating unit configured to generate a parity table based on the measurement value equation and the parity equation, wherein the parity table is used to indicate the number of faulty IMU sensors in the positioning system.
Optionally, the third obtaining unit includes: a third determination module to determine a relative pose prediction result for the target object based on the velocity data; a fourth determination module to determine a pose observation of the target object based on the second measurement data; and the second acquisition module is used for fusing the relative attitude prediction result and the attitude observation result to obtain the current attitude of the target object.
According to another aspect of the embodiments of the present invention, there is also provided a positioning system, including: a plurality of inertial sensors IMU for acquiring first measurement data of a target object; the fusion equipment is used for fusing the first measurement data to obtain the speed data of the target object; other sensors for acquiring second measurement data of the target object, wherein the other sensors are sensors of the positioning system except the inertial sensor IMUs; and the controller is used for fusing the speed data and the second measurement data by using any one of the positioning methods to obtain the current posture of the target object.
Optionally, the positioning system further comprises: and the alarm is used for generating alarm information when the IMU sensor which is not less than a preset value in the plurality of IMU sensors fails.
Optionally, the positioning system further comprises: a compensator for compensating an acceleration error of the target object.
Optionally, the positioning system further comprises: a parity checker to represent a state of the plurality of IMU sensors.
According to another aspect of the embodiment of the present invention, there is also provided a computer-readable storage medium, where the computer-readable storage medium includes a stored program, and when the program runs, the apparatus where the storage medium is located is controlled to execute any one of the above positioning methods.
According to another aspect of the embodiment of the present invention, there is also provided a processor, configured to execute a program, where the program executes to perform the positioning method described in any one of the above.
According to another aspect of an embodiment of the present invention, there is also provided an autonomous vehicle including: the positioning system of any of the above, further comprising: a memory, a processor coupled with the memory, the memory and the processor communicating over a bus system; the memory is used for storing a program, wherein the program, when executed by the processor, controls the device in which the memory is located to execute any one of the positioning methods; the processor is configured to execute a program, where the program executes the positioning method described in any one of the above.
In the embodiment of the invention, first measurement data of a target object are fused to obtain speed data of the target object, wherein the first measurement data are motion data of the target object, which are acquired by at least two inertial sensors IMU; acquiring second measurement data of the target object, wherein the second measurement data is motion data of the target object acquired by other sensors except at least two IMU sensors in the positioning system; and fusing the speed data and the second measurement data to obtain the current attitude of the target object. By the positioning method provided by the embodiment of the invention, the aim of obtaining the current posture of the target object by setting the plurality of IMU sensors in the positioning system and fusing all or part of the measurement data acquired by the IMU sensors of the plurality of IMU sensors to fuse the fused measurement data with the measurement data acquired by other sensors is fulfilled, the technical effect of improving the positioning precision is achieved, and the technical problems that the working state of an IMU device cannot be effectively detected and fed back in a positioning scheme by using the IMU in the related technology, and when the IMU device fails, the IMU device cannot be found in time and the potential safety hazard exists when the IMU device is still used for positioning are solved.
Drawings
The accompanying drawings, which are included to provide a further understanding of the invention and are incorporated in and constitute a part of this application, illustrate embodiment(s) of the invention and together with the description serve to explain the invention without limiting the invention. In the drawings:
FIG. 1 is a flow chart of IMU based positioning according to the prior art;
FIG. 2 is a flow chart of a positioning method according to an embodiment of the invention;
FIG. 3 is a schematic view of an IMU sensor installation according to an embodiment of the present invention;
FIG. 4 is a schematic view of a positioning device according to an embodiment of the invention;
FIG. 5 is a schematic view of a positioning system according to an embodiment of the invention;
FIG. 6 is a schematic representation of the conversion of auxiliary IMU sensor measurements into a corresponding coordinate system of the primary IMU sensor in accordance with an embodiment of the present invention;
FIG. 7 is a block diagram of an alternative positioning system in accordance with an embodiment of the present invention.
Detailed Description
In order to make the technical solutions of the present invention better understood, the technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are only a part of the embodiments of the present invention, and not all of the embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
It should be noted that the terms "first," "second," and the like in the description and claims of the present invention and in the drawings described above are used for distinguishing between similar elements and not necessarily for describing a particular sequential or chronological order. It is to be understood that the data so used is interchangeable under appropriate circumstances such that the embodiments of the invention described herein are capable of operation in sequences other than those illustrated or described herein. Furthermore, the terms "comprises," "comprising," and "having," and any variations thereof, are intended to cover a non-exclusive inclusion, such that a process, method, system, article, or apparatus that comprises a list of steps or elements is not necessarily limited to those steps or elements expressly listed, but may include other steps or elements not expressly listed or inherent to such process, method, article, or apparatus.
Example 1
In accordance with an embodiment of the present invention, there is provided a method embodiment of a positioning method, it should be noted that the steps illustrated in the flowchart of the figure may be performed in a computer system such as a set of computer executable instructions and that, although a logical order is illustrated in the flowchart, in some cases, the steps illustrated or described may be performed in an order different than that herein.
Fig. 2 is a flowchart of a positioning method according to an embodiment of the present invention, as shown in fig. 2, the positioning method includes the following steps:
step S202, fusing first measurement data of the target object to obtain speed data of the target object, wherein the first measurement data are motion data of the target object, acquired by at least two inertial sensors IMU.
Optionally, the target object is an object that needs to be located, for example, an autonomous vehicle, a logistics robot, a dining robot, an unmanned aerial vehicle, and the like.
Optionally, the first measurement data is motion information of the target object acquired by the inertia sensor IMU, and the target object may be located based on the data.
It should be noted that, compared to the prior art in which the positioning system has only one IMU sensor, as a high-precision sensor which is easily affected by extreme temperatures (high or low), severe vibrations, collisions, and the like in a long-time working state and can be irreversibly damaged, it is easy to have a drawback that accurate positioning cannot be performed when an IMU sensor in the positioning system fails.
Further, it should be noted that the speed data may be an acceleration measurement value.
Step S204, second measurement data of the target object is obtained, wherein the second measurement data is motion data of the target object acquired by other sensors in the positioning system except the at least two IMU sensors.
Optionally, the other sensors of the positioning system than the at least two IMU sensors may include, but are not limited to: wheel encoders, global satellite navigation positioning systems, three-dimensional laser radars, high-precision maps, and the like.
And S206, fusing the speed data and the second measurement data to obtain the current posture of the target object.
As can be seen from the above, in the embodiment of the present invention, the first measurement data of the target object is fused to obtain the velocity data of the target object, where the first measurement data is the motion data of the target object acquired by the at least two inertial sensors IMU; acquiring second measurement data of the target object, wherein the second measurement data is motion data of the target object acquired by other sensors except at least two IMU sensors in the positioning system; the speed data and the second measurement data are fused to obtain the current posture of the target object, the purpose that the fused measurement data and the measurement data collected by other sensors are fused to obtain the current posture of the target object is achieved by arranging the plurality of IMU sensors in the positioning system and fusing the measurement data collected by all or part of the IMU sensors of the plurality of IMU sensors, and the technical effect of improving the positioning precision is achieved.
Therefore, the positioning method provided by the embodiment of the invention solves the technical problems that in the scheme of positioning by using the IMU in the related technology, the working state of the IMU device cannot be effectively detected and fed back, when the IMU device fails, the IMU device cannot be found in time, and potential safety hazards exist when the IMU device is still positioned by using data acquired by the IMU.
It should be noted that, in the embodiment of the present invention, 3 IMU sensors in the positioning system are taken as an example for description. In order to more effectively perform mutual verification of multiple IMU sensors, a triangular method can be used for installing 3 IMU sensors on a positioning carrier, and the 3 IMU sensors are prevented from being in a straight line as much as possible.
Further, there may be 1 primary IMU sensor of the 3 IMU sensors described above, i.e., IMU 02 auxiliary IMU sensors, i.e. IMU1、IMU2. Fig. 3 is a schematic view of an IMU sensor according to an embodiment of the present invention, and the 3 IMU sensors may be installed in a triangular shape as shown in fig. 3.
As an optional embodiment, before the fusing the first measurement data of the target object to obtain the speed data of the target object, the positioning method further includes: acquiring first measurement data of a target object; acquiring a data identifier of the first measurement data; determining the total number of IMU sensors which normally work in the positioning system based on the data identification; and generating alarm information under the condition that the total quantity is less than a preset value.
In this embodiment, which IMU sensors in the positioning system are not in operation may be determined according to the acquired first measurement data of the target object, and in a case that the total number of IMU sensors capable of operating normally in the positioning system is less than a predetermined value, an alarm message may be generated.
For example, when there are 3 IMU sensors in the positioning system, if there are 1 IMU sensor that has a fault, the positioning system may still fuse the measurement data acquired by 2 IMUs to obtain the measurement values of acceleration and/or angular velocity; if 2 IMU sensors have faults, the positioning system can only receive the measurement data acquired by 1 IMU sensor, and data fusion cannot be carried out at the moment.
As an alternative embodiment, fusing the first measurement data of the target object to obtain the speed data of the target object, includes: converting first measurement data acquired by a secondary IMU sensor in the at least two IMU sensors into a main coordinate system corresponding to a main IMU sensor in the at least two IMU sensors; and obtaining speed data based on the measurement data, the weighting matrix and the conversion matrix in the main coordinate system.
Here, the first measurement data collected by the secondary IMU sensor of the two IMU sensors may be converted into the main coordinate system corresponding to the main IMU sensor, so that the velocity data may be obtained based on the measurement data, the weighting matrix, and the conversion matrix in the main coordinate system.
When the speed data is the acceleration of the target object in the X axis of the main coordinate system, the speed data is obtained based on the measurement data, the weighting matrix and the transformation matrix in the main coordinate system, and the method comprises the following steps: determining the X-axis acceleration of the target object in the main coordinate system through a first formula, wherein the first formula is as follows: and y is equal to Hx, wherein y represents the X-axis acceleration measured value of the target object in the main coordinate system, H represents the conversion matrix, and X represents the X-axis acceleration of the target object in the main coordinate system.
Here, mainly for recovering a relatively accurate true acceleration/angular velocity value using a plurality of healthy IMU vehicle values, the X-axis acceleration is taken as an example, and y is Hx, where y is [ ax ]0，ax1，ax2]TIs an X-axis acceleration measurement of three IMUs, H ═ 1, 1]TIs the transformation matrix and X-ax is the true X-axis acceleration value.
As an alternative embodiment, obtaining the speed data based on the measurement data, the weighting matrix and the transformation matrix in the main coordinate system includes: determining the X-axis acceleration of the target object in the main coordinate system through a second formula, wherein the second formula is as follows:
where x is ax and W represents a weighting matrix.
Wherein, the weighting matrix is determined according to the standard deviation of the acceleration noise on the X-axis coordinate in the main coordinate system. In particular, the amount of the solvent to be used,
in the formula, sigma0，σ1And σ2Are respectively IMU0、IMU1And IMU2Standard deviation of X-axis acceleration noise.
As an optional embodiment, after the fusing the first measurement data of the target object to obtain the speed data of the target object, the positioning method further includes: the standard deviation of the acceleration noise is updated.
In this embodiment, after the first measurement data is fused to obtain a more reliable true value ax of the acceleration, the corresponding standard deviation of the output noise also needs to be updated, specifically,
it should be noted that if the same type of IMU sensor is used in the positioning system, σ can be considered as1＝σ2And σ3Then, there are
According to this equation, if there are 3 healthy IMU sensors, the output noise standard deviation will become the original one
If there are 2 healthy IMU sensors, the output noise standard deviation will become the original one
And performing multi-data fusion by using the IMU sensors, and performing weighted average on data of the IMU sensors to obtain an optimal measured value of the acceleration and the angular velocity.
As an optional embodiment, the positioning method further comprises: converting first measurement data acquired by a secondary IMU sensor in the at least two IMU sensors into a main coordinate system corresponding to a main IMU sensor in the at least two IMU sensors; constructing a measurement value equation and a parity equation based on the measurement data in the coordinate system; a parity table is generated based on the measurement value equation and the parity equation, wherein the parity table is used to represent the number of IMU sensors in the positioning system that have failed.
For example, after the measurement data of 3 IMU sensors can be converted into the same reference coordinate system (i.e., the coordinate system corresponding to the primary IMU sensor), a measurement equation can be constructed, using X-axis acceleration as an example: [ ax ]0，ax1，ax2]T＝[1，1，1]ax, wherein0，ax1，ax2Are respectively IMU0、IMU1And IMU2The accelerometer's X-axis acceleration measurement, ax, is the true acceleration measurement. The parity equation can then be constructed: k is a radical of0：ax0-ax1＝0；k1：ax0-ax2＝0；k2：ax1-ax 20. When the equation is satisfied, setting the corresponding parity value to be 0, otherwise setting the parity value to be 1, and then establishing a parity table to clearly represent the working condition of the IMU sensor, wherein the parity table is shown in the following table 1:
TABLE 1
Here, it should be noted that the parity table is established based on that the data of 3 IMUs can be received normally, time synchronization is performed on the 3 IMUs, and there is no serious data delay in the IMUs themselves. If the data of only one IMU can be received, only the IMU data is used for positioning, and no IMU redundancy exists at the moment; if only two IMU data can be received, whether the IMU is damaged or not can be judged, alarm information can be given when the IMU is damaged, and the damaged IMU cannot be found out accurately.
As an optional embodiment, fusing the speed data and the second measurement data to obtain the current posture of the target object, includes: determining a relative pose prediction result of the target object based on the velocity data; determining a pose observation of the target object based on the second measurement data; and fusing the relative attitude prediction result and the attitude observation result to obtain the current attitude of the target object.
Therefore, the positioning method provided by the embodiment of the invention can effectively feed back the working state of the IMU sensor in time; in the embodiment of the invention, three IMU sensors are orthogonally arranged on the positioning carrier, and then data acquired by the three IMU sensors are converted into the same coordinate system to carry out parity check, so that the working state of the IMU sensors can be checked. If the IMU is damaged, the positioning method provided by the embodiment of the invention can detect in time and perform corresponding feedback and processing. The reliability of the positioning system can be greatly improved compared to a positioning system of a single IMU. In addition, because the measured values of a plurality of healthy IMUs are used for fusing the measured value of the acceleration and the angular velocity, when the noise of a single IMU is large, the measured values of other IMUs are used for compensating part of the noise to obtain a better IMU measured value, and therefore the measurement accuracy of the acceleration and the angular velocity can be effectively improved. Moreover, the low-cost IMU has higher data noise, more rigorous requirements on the use environment and higher possibility of causing problems by a single low-cost IMU, and if the positioning method in the embodiment of the invention is used, the reliability and the precision of the positioning system can be obviously improved.
Example 2
According to another aspect of the embodiment of the present invention, there is also provided a positioning apparatus, and fig. 4 is a schematic view of the positioning apparatus according to the embodiment of the present invention, as shown in fig. 4, the positioning apparatus may include: a first acquisition unit 41, a second acquisition unit 43 and a third acquisition unit 45. The positioning device will be explained below.
The first obtaining unit 41 is configured to fuse first measurement data of the target object to obtain speed data of the target object, where the first measurement data is motion data of the target object acquired by at least two inertial sensors IMU.
A second obtaining unit 43 for obtaining second measurement data of the target object, wherein the second measurement data is the motion data of the target object acquired by the other sensors of the positioning system except the at least two IMU sensors.
And a third obtaining unit 45, configured to fuse the speed data and the second measurement data to obtain a current posture of the target object.
It should be noted here that the first acquiring unit 41, the second acquiring unit 43, and the third acquiring unit 45 correspond to steps S202 to S206 in embodiment 1, and the modules are the same as the corresponding steps in the implementation example and the application scenario, but are not limited to the disclosure in embodiment 1. It should be noted that the modules described above as part of an apparatus may be implemented in a computer system such as a set of computer-executable instructions.
As can be seen from the above, in the above embodiments of the present application, the first obtaining unit may be used to fuse the first measurement data of the target object to obtain the speed data of the target object, where the first measurement data is the motion data of the target object acquired by the at least two inertial sensors IMU; then, second measurement data of the target object are obtained by a second obtaining unit, wherein the second measurement data are motion data of the target object, which are collected by other sensors except at least two IMU sensors in the positioning system; and fusing the speed data and the second measurement data by using a third acquisition unit to obtain the current posture of the target object. By the positioning device provided by the embodiment of the invention, the aim of obtaining the current posture of the target object by arranging the plurality of IMU sensors in the positioning system and fusing all or part of the measurement data acquired by the IMU sensors of the plurality of IMU sensors to fuse the fused measurement data with the measurement data acquired by other sensors is fulfilled, the technical effect of improving the positioning precision is achieved, and the technical problems that the working state of an IMU device cannot be effectively detected and fed back in a positioning scheme by using the IMU in the related technology, and when the IMU device fails, the IMU device cannot be found in time and the potential safety hazard exists when the IMU device is still used for positioning are solved.
Optionally, the positioning device further comprises: the fourth acquisition unit is used for acquiring the first measurement data of the target object before the first measurement data of the target object is fused to obtain the speed data of the target object; a fifth obtaining unit, configured to obtain a data identifier of the first measurement data; the determining unit is used for determining the total number of IMU sensors which normally work in the positioning system based on the data identification; and the generating unit is used for generating alarm information under the condition that the total quantity is less than a preset value.
Optionally, the first obtaining unit includes: the conversion module is used for converting first measurement data acquired by a secondary IMU sensor in the at least two IMU sensors into a main coordinate system corresponding to a main IMU sensor in the at least two IMU sensors; and the first acquisition module is used for acquiring the speed data based on the measurement data, the weighting matrix and the conversion matrix in the main coordinate system.
Optionally, when the speed data is an X-axis acceleration of the target object in the main coordinate system, the obtaining module includes: the first determining module is used for determining the X-axis acceleration of the target object in the main coordinate system through a first formula, wherein the first formula is as follows: and y is equal to Hx, wherein y represents the X-axis acceleration measured value of the target object in the main coordinate system, H represents the conversion matrix, and X represents the X-axis acceleration of the target object in the main coordinate system.
Optionally, the obtaining module includes: the second determining module is used for determining the X-axis acceleration of the target object in the main coordinate system through a second formula, wherein the second formula is as follows:
where x is ax and W represents a weighting matrix.
Alternatively, the weighting matrix is determined from the standard deviation of the acceleration noise on the X-axis coordinate in the master coordinate system.
Optionally, the positioning device further comprises: and the updating unit is used for updating the standard deviation of the acceleration noise after the first measurement data of the target object is fused to obtain the speed data of the target object.
Optionally, the positioning device further comprises: the conversion unit is used for converting first measurement data acquired by a secondary IMU sensor in the at least two IMU sensors into a main coordinate system corresponding to a main IMU sensor in the at least two IMU sensors; a construction unit for constructing a measurement value equation and a parity equation based on the measurement data in the coordinate system; and the generating unit is used for generating a parity table based on the measurement value equation and the parity equation, wherein the parity table is used for indicating the number of IMU sensors with faults in the positioning system.
Optionally, the third obtaining unit includes: a third determination module to determine a relative pose prediction result for the target object based on the velocity data; a fourth determination module for determining an attitude observation of the target object based on the second measurement data; and the second acquisition module is used for fusing the relative attitude prediction result and the attitude observation result to obtain the current attitude of the target object.
Example 3
According to another aspect of the embodiment of the present invention, there is also provided a positioning system, and fig. 5 is a schematic diagram of a positioning system according to an embodiment of the present invention, as shown in fig. 5, the positioning system may include: a plurality of inertial sensors IMU51 for acquiring first measurement data of a target object; the fusion device 53 is configured to fuse the first measurement data to obtain speed data of the target object; a further sensor 55 for acquiring second measurement data of the target object, wherein the further sensor is a sensor of the positioning system other than the plurality of inertial sensors IMU; the controller 57 is configured to fuse the velocity data and the second measurement data by using the positioning method according to any one of the embodiments 1 to obtain the current posture of the target object. By the positioning system provided by the embodiment of the invention, the aim of obtaining the current posture of the target object by fusing the fused measurement data and the measurement data acquired by other sensors by arranging the plurality of IMU sensors in the positioning system and fusing the measurement data acquired by all or part of the IMU sensors of the plurality of IMU sensors is fulfilled, and the technical effect of improving the positioning precision is achieved.
As an alternative embodiment, the positioning system further comprises: and the alarm is used for generating alarm information when the IMU sensor which is not less than a preset value in the plurality of IMU sensors fails.
For example, when there are 3 IMU sensors in the positioning system, if it is determined that there are 2 or 3 IMU sensors that are malfunctioning, the alarm may generate alarm information to indicate that the IMU sensor that exceeds a predetermined value is malfunctioning.
As an alternative embodiment, the positioning system further comprises: and the compensator is used for compensating the acceleration error of the target object.
As an alternative embodiment, the positioning system further comprises: a parity checker to represent a state of the plurality of IMU sensors.
As can be seen from the above, the positioning system in the embodiment of the present invention increases the number of IMU sensors, for example, two IMU sensors (one master IMU) may be added, compared to the disadvantage that only a single IMU sensor in the related art cannot detect the failure of the IMU sensor0) Two aids (IMU)1、IMU2) Therefore, mutual verification of multiple IMUs can be effectively carried out.
In addition, in an embodiment of the present invention, the positioning system may include: a lever arm compensation module (i.e., a compensator), a parity check module (i.e., a parity checker), a data anomaly alarm module (i.e., an alarm), and a multi-IMU data fusion module (i.e., a fusion device). For example, sensor redundancy can be realized by three IMU sensors, lever arm values of two IMU sensors are compensated, the lever arm values are converted into a coordinate system corresponding to one IMU sensor, parity check is performed on outputs (including gyroscope and accelerometer data) of the three IMU sensors, the number of abnormal IMU sensors is detected, and influences of abnormal data are eliminated or an alarm responding is given.
The lever arm in the lever arm compensation module refers to a vector between two auxiliary IMU sensors and a main IMU sensor, and due to the existence of the lever arm, measurement values of the two auxiliary IMU sensors need to be converted into a coordinate system of the main IMU sensor before verification. Since the three IMU sensors are placed on a rigid body, their angular velocity measurements are free of lever arm errors, only the lever arm errors of acceleration need to be compensated, and then the acceleration and angular velocity are translated into the master IMU coordinate system. FIG. 6 is a schematic diagram of the transformation of the IMU sensor measurements into the coordinate system corresponding to the primary IMU sensor, according to an embodiment of the present invention, as shown in FIG. 6, the primary IMU coordinate system may be kept stationary, and the transformation of acceleration and angular velocity into the primary IMU coordinate system may be achieved by rotating the secondary IMU coordinate system, such that
Here can beThe centrifugal acceleration caused by the angular velocity is calculated in the following manner:
wherein, here acRepresenting centrifugal acceleration, wrawThe angular velocity is represented by the angular velocity,
a lever arm vector is represented. Then the tangential acceleration (or euler) caused by the angular acceleration is calculated:
here, the
The derivative of the angular velocity is indicated. And calculates the lever arm error of acceleration: a islever_arm_error＝ac+at(ii) a The acceleration lever arm error can be compensated for by: a iscomp＝araw+alever_arm_errorAnd rotating the measurements of the secondary IMU sensor into the primary IMU coordinate system by:
second, the parity module may construct a measurement equation after converting the measurements of the secondary IMU sensor into the primary IMU sensor, using X-axis acceleration as an example: [ ax ]0，ax1，ax2]T＝[1，1，1]ax, wherein0，ax1，ax2Are respectively IMU0、IMU1And IMU2The accelerometer's X-axis acceleration measurement, ax, is the true acceleration measurement. The parity equation can then be constructed: k is a radical of0：ax0-ax1＝0；k1：ax0-ax2＝0；k2：ax1-ax 20. When the equation is satisfied, the corresponding parity value is set to 0, otherwise to 1, and then a parity table is established to clearly show the operation of the IMU sensor, where the parity table is oddThe even table can be table 1 in example 1 above.
Then, the alarm in the embodiment of the invention can accurately control the number of damaged IMU sensors in the positioning system on the basis of the parity check module; for example, when there are three IMU sensors in the positioning system, the positioning system may fuse the data of the three IMU sensors to construct an optimal acceleration/angular velocity measurement when there is no IMU damage; when detecting that one IMU sensor is damaged, the damaged IMU sensor can be accurately found, and the measured values of the other two healthy IMU sensors are fused and positioned to give an alarm signal to the damaged IMU sensor; when 2 or 3 IMU sensors are detected as defective, a severe alarm signal may be triggered, although the defective IMU sensors may not be accurately found. That is, in the embodiment of the present invention, when the processing manner of the abnormal IMU sensor is that 0 IMU sensor is abnormal, the measurement values of 3 IMU sensors may be used for positioning; when 1 IMU sensor is abnormal, 2 healthy IMUs can be used for positioning, and abnormal IMU sensor information is alarmed; and when 2 or 3 IMU sensors are abnormal, a serious alarm can be given.
Finally, the multi-IMU data fusion module is described in detail in embodiment 1 above, and is not described here again.
FIG. 7 is a block diagram of an alternative positioning system in which there may be 3 individual IMU sensors and other sensors, as shown in FIG. 7, according to an embodiment of the present invention; two of the 3 IMU sensors are connected with a lever arm compensation module for performing lever arm value compensation, and one IMU sensor is connected with a parity check module for performing parity check so as to judge the number of abnormal IMU sensors; when 2 or 3 IMU sensors are detected to have faults, data abnormity alarming is carried out; when 1 IMU sensor fault is detected, performing data fusion on the measured values of the remaining 2 healthy IMU sensors; when 3 IMU data fusion is detected, data fusion is carried out on the measured value of the IMU sensor, acceleration and angular velocity integration is carried out on the fused data to obtain a relative attitude prediction result of the target object, and the relative attitude prediction result is fused with attitude observation results obtained based on other sensors to obtain the attitude of the target object at the current moment.
It should be noted that, in the embodiment of the present invention, 3 IMU sensors are used in a triangular vertex manner, and other mounting positions may be used, which is not specifically limited in the embodiment of the present invention; for example, checksum compensation for multiple IMU sensors may be achieved using 2 or 4, or even more IMU sensors; the use of 3 IMU sensors here is considered based on cost and demand.
In summary, in the embodiment of the present invention, in order to improve the robustness of the positioning system in different scenarios, a set of reliable alternative attitude prediction schemes is provided, so that the redundancy of the IMU sensor in the related art is effectively reduced, and when the IMU sensor is abnormal, only a new IMU sensor is replaced, which may cause serious consequences for some products with high positioning requirements, such as automatic driving.
Example 4
According to another aspect of the embodiments of the present invention, there is also provided a computer-readable storage medium, which includes a stored program, where the program, when executed, controls an apparatus in which the storage medium is located to perform any one of the above positioning methods.
Example 5
According to another aspect of the embodiment of the present invention, there is provided a processor, configured to execute a program, where the program executes to perform any one of the above positioning methods.
Example 6
According to another aspect of an embodiment of the present invention, there is also provided an autonomous vehicle including: the positioning system of any of the above, further comprising: a memory, a processor coupled to the memory, the memory and the processor communicating via a bus system; the memory is used for storing a program, wherein the program controls the equipment where the memory is located to execute any one of the positioning methods when being executed by the processor; the processor is used for running a program, wherein the program executes any one of the positioning methods.
The above-mentioned serial numbers of the embodiments of the present invention are merely for description and do not represent the merits of the embodiments.
In the above embodiments of the present invention, the descriptions of the respective embodiments have respective emphasis, and for parts that are not described in detail in a certain embodiment, reference may be made to related descriptions of other embodiments.
In the embodiments provided in the present application, it should be understood that the disclosed technology can be implemented in other ways. The above-described embodiments of the apparatus are merely illustrative, and for example, the division of the units may be a logical division, and in actual implementation, there may be another division, for example, multiple units or components may be combined or integrated into another system, or some features may be omitted, or not executed. In addition, the shown or discussed mutual coupling or direct coupling or communication connection may be an indirect coupling or communication connection through some interfaces, units or modules, and may be in an electrical or other form.
The units described as separate parts may or may not be physically separate, and parts displayed as units may or may not be physical units, may be located in one place, or may be distributed on a plurality of units. Some or all of the units can be selected according to actual needs to achieve the purpose of the solution of the embodiment.
In addition, functional units in the embodiments of the present invention may be integrated into one processing unit, or each unit may exist alone physically, or two or more units are integrated into one unit. The integrated unit can be realized in a form of hardware, and can also be realized in a form of a software functional unit.
The integrated unit, if implemented in the form of a software functional unit and sold or used as a stand-alone product, may be stored in a computer readable storage medium. Based on such understanding, the technical solution of the present invention may be embodied in the form of a software product, which is stored in a storage medium and includes instructions for causing a computer device (which may be a personal computer, a server, or a network device) to execute all or part of the steps of the method according to the embodiments of the present invention. And the aforementioned storage medium includes: a U-disk, a Read-Only Memory (ROM), a Random Access Memory (RAM), a removable hard disk, a magnetic or optical disk, and other various media capable of storing program codes.
The foregoing is only a preferred embodiment of the present invention, and it should be noted that, for those skilled in the art, various modifications and decorations can be made without departing from the principle of the present invention, and these modifications and decorations should also be regarded as the protection scope of the present invention.
Claims (17)
1. A method of positioning, comprising:
fusing first measurement data of a target object to obtain speed data of the target object, wherein the first measurement data are motion data of the target object, acquired by at least two inertial sensors IMUs;
acquiring second measurement data of the target object, wherein the second measurement data is the motion data of the target object acquired by other sensors in the positioning system except the at least two IMU sensors;
and fusing the speed data and the second measurement data to obtain the current posture of the target object.
2. The method of claim 1, wherein prior to fusing the first measurement data of the target object to obtain the velocity data of the target object, the method further comprises:
acquiring first measurement data of the target object;
acquiring a data identifier of the first measurement data;
determining a total number of IMU sensors in the positioning system that are operating properly based on the data identification;
and generating alarm information under the condition that the total number is less than a preset value.
3. The method of claim 1, wherein fusing the first measurement data of the target object to obtain the velocity data of the target object comprises:
converting first measurement data acquired by a secondary IMU sensor of the at least two IMU sensors into a main coordinate system corresponding to a main IMU sensor of the at least two IMU sensors;
and obtaining the speed data based on the measurement data, the weighting matrix and the conversion matrix in the main coordinate system.
4. The method of claim 3, wherein obtaining the velocity data based on the measurement data, the weighting matrix, and the transformation matrix in the main coordinate system when the velocity data is an X-axis acceleration of the target object in the main coordinate system comprises:
determining the X-axis acceleration of the target object in the main coordinate system through a first formula, wherein the first formula is as follows: and y is Hx, wherein y represents the X-axis acceleration measured value of the target object in the main coordinate system, H represents the conversion matrix, and X represents the X-axis acceleration of the target object in the main coordinate system.
5. The method of claim 4, wherein deriving the velocity data based on the measurement data, a weighting matrix, and a transformation matrix in the master coordinate system comprises:
determining the X-axis acceleration of the target object in the main coordinate system through a second formula, wherein the second formula is as follows:
where x is ax and W represents the weighting matrix.
6. The method of claim 5, wherein the weighting matrix is determined according to a standard deviation of acceleration noise on an X-axis coordinate in the master coordinate system.
7. The method of claim 6, wherein after fusing the first measurement data of the target object to obtain the velocity data of the target object, the method further comprises:
and updating the standard deviation of the acceleration noise.
8. The method according to any one of claims 1 to 7, further comprising:
converting first measurement data acquired by a secondary IMU sensor of the at least two IMU sensors into a main coordinate system corresponding to a main IMU sensor of the at least two IMU sensors;
constructing a measurement value equation and a parity equation based on the measurement data in the coordinate system;
generating a parity table based on the measurement equation and the parity equation, wherein the parity table is used to represent the number of IMU sensors in the positioning system that have failed.
9. The method of any one of claims 1 to 7, wherein fusing the velocity data and the second measurement data to obtain a current pose of the target object comprises:
determining a relative pose prediction result of the target object based on the velocity data;
determining a pose observation of the target object based on the second measurement data;
and fusing the relative attitude prediction result and the attitude observation result to obtain the current attitude of the target object.
10. A positioning device, comprising:
the system comprises a first acquisition unit, a second acquisition unit and a third acquisition unit, wherein the first acquisition unit is used for fusing first measurement data of a target object to obtain speed data of the target object, and the first measurement data are motion data of the target object acquired by at least two inertial sensors IMU;
a second obtaining unit, configured to obtain second measurement data of the target object, where the second measurement data is motion data of the target object acquired by a sensor other than the at least two IMU sensors in the positioning system;
and the third acquisition unit is used for fusing the speed data and the second measurement data to obtain the current posture of the target object.
11. A positioning system, comprising:
a plurality of inertial sensors IMU for acquiring first measurement data of a target object;
the fusion equipment is used for fusing the first measurement data to obtain the speed data of the target object;
other sensors for acquiring second measurement data of the target object, wherein the other sensors are sensors of the positioning system except the inertial sensor IMUs;
a controller for fusing the velocity data and the second measurement data to obtain a current attitude of the target object by using the positioning method according to any one of claims 1 to 9.
12. The positioning system of claim 11, further comprising: and the alarm is used for generating alarm information when the IMU sensor which is not less than a preset value in the plurality of IMU sensors fails.
13. The positioning system of claim 12, further comprising: a compensator for compensating an acceleration error of the target object.
14. The positioning system of claim 13, further comprising: a parity checker to represent a state of the plurality of IMU sensors.
15. A computer-readable storage medium, comprising a stored program, wherein the program, when executed, controls an apparatus in which the storage medium is located to perform the positioning method according to any one of claims 1 to 9.
16. A processor, characterized in that the processor is configured to run a program, wherein the program is configured to execute the positioning method according to any one of claims 1 to 9 when running.
17. An autonomous vehicle, comprising: the positioning system of any of the preceding claims 11 to 14, further comprising:
a memory, a processor coupled with the memory, the memory and the processor communicating over a bus system;
the memory is used for storing a program, wherein the program when executed by the processor controls the device in which the memory is located to execute the positioning method according to any one of claims 1 to 9;
the processor is configured to execute a program, wherein the program executes the positioning method according to any one of claims 1 to 9.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202110611125.8A CN113324541B (en) | 2021-06-01 | 2021-06-01 | Positioning method, positioning device and positioning system |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202110611125.8A CN113324541B (en) | 2021-06-01 | 2021-06-01 | Positioning method, positioning device and positioning system |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN113324541A true CN113324541A (en) | 2021-08-31 |
| CN113324541B CN113324541B (en) | 2024-05-31 |
Family
ID=77423094
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN202110611125.8A Active CN113324541B (en) | 2021-06-01 | 2021-06-01 | Positioning method, positioning device and positioning system |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN113324541B (en) |
Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN114415671A (en) * | 2021-12-28 | 2022-04-29 | 上海擎朗智能科技有限公司 | Method for detecting whether sensor of robot fails or not and robot |
| CN114877913A (en) * | 2022-05-20 | 2022-08-09 | 广州小马智行科技有限公司 | Non-orthogonal error calibration method, device, equipment and medium for inertial measurement unit |
Citations (6)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US20080262729A1 (en) * | 2007-04-18 | 2008-10-23 | Honeywell International Inc. | Inertial measurement unit fault detection isolation reconfiguration using parity logic |
| CN103389088A (en) * | 2013-07-24 | 2013-11-13 | 北京航空航天大学 | Determination method of optimal configuration scheme of four-redundancy strapdown inertial navigation system (RFINS) |
| CN105424035A (en) * | 2015-10-30 | 2016-03-23 | 北京航天控制仪器研究所 | Inertial measurement system multi-sensor redundancy method |
| CN105628024A (en) * | 2015-12-29 | 2016-06-01 | 中国电子科技集团公司第二十六研究所 | Single person positioning navigator based on multi-sensor fusion and positioning and navigating method |
| US20180372498A1 (en) * | 2017-06-21 | 2018-12-27 | Caterpillar Inc. | System and method for determining machine state using sensor fusion |
| CN112082544A (en) * | 2019-06-12 | 2020-12-15 | 杭州海康汽车技术有限公司 | IMU data compensation method and device |
-
2021
- 2021-06-01 CN CN202110611125.8A patent/CN113324541B/en active Active
Patent Citations (6)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US20080262729A1 (en) * | 2007-04-18 | 2008-10-23 | Honeywell International Inc. | Inertial measurement unit fault detection isolation reconfiguration using parity logic |
| CN103389088A (en) * | 2013-07-24 | 2013-11-13 | 北京航空航天大学 | Determination method of optimal configuration scheme of four-redundancy strapdown inertial navigation system (RFINS) |
| CN105424035A (en) * | 2015-10-30 | 2016-03-23 | 北京航天控制仪器研究所 | Inertial measurement system multi-sensor redundancy method |
| CN105628024A (en) * | 2015-12-29 | 2016-06-01 | 中国电子科技集团公司第二十六研究所 | Single person positioning navigator based on multi-sensor fusion and positioning and navigating method |
| US20180372498A1 (en) * | 2017-06-21 | 2018-12-27 | Caterpillar Inc. | System and method for determining machine state using sensor fusion |
| CN112082544A (en) * | 2019-06-12 | 2020-12-15 | 杭州海康汽车技术有限公司 | IMU data compensation method and device |
Non-Patent Citations (2)
| Title |
|---|
| 张国光等: "基于GPS/惯性导航的船载平台导引和显示系统的实现", 《信息通信》 * |
| 李延龙等: "一种冗余配置的惯性导航系统渐变型故障容错方法", 《弹箭与制导学报》 * |
Cited By (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN114415671A (en) * | 2021-12-28 | 2022-04-29 | 上海擎朗智能科技有限公司 | Method for detecting whether sensor of robot fails or not and robot |
| CN114877913A (en) * | 2022-05-20 | 2022-08-09 | 广州小马智行科技有限公司 | Non-orthogonal error calibration method, device, equipment and medium for inertial measurement unit |
| CN114877913B (en) * | 2022-05-20 | 2024-05-07 | 广州小马智行科技有限公司 | Non-orthogonal error calibration method, device, equipment and medium of inertial measurement unit |
Also Published As
| Publication number | Publication date |
|---|---|
| CN113324541B (en) | 2024-05-31 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| US8855867B2 (en) | Vehicle sensor node | |
| CN104880722B (en) | The GPS velocity and position detection rejecting outliers method of unmanned plane | |
| CN113324541B (en) | Positioning method, positioning device and positioning system | |
| US20160209236A1 (en) | Method, fusion filter, and system for fusing sensor signals with different temporal signal output delays into a fusion data set | |
| KR101135782B1 (en) | System for navigation redundancy | |
| CN105698788B (en) | System and method for generating two independent and distinct attitude solutions, inertial solutions, or both | |
| CN111102978A (en) | Method and device for determining vehicle motion state and electronic equipment | |
| KR20140067108A (en) | Time-corrected sensor system | |
| US20170089722A1 (en) | Method and system for initializing a sensor fusion system | |
| CN105571585B (en) | System and method for isolating attitude faults in aircraft | |
| JPH06102053A (en) | Trouble-permission inertial navigation system | |
| CN105264387A (en) | Method for determining at least one speed in a rail vehicle | |
| US10267638B2 (en) | Method and system for adapting a navigation system | |
| JP2013049408A (en) | Method and system for determining flight parameter of aircraft | |
| KR20150093846A (en) | Device for outputting a measurement signal indicating a physical measurement variable | |
| JP2019128639A (en) | Electronic control device | |
| CN111352433B (en) | Fault diagnosis method for horizontal attitude angle of unmanned aerial vehicle | |
| US20210035456A1 (en) | Unmanned aircraft, and method and system for navigation | |
| WO2018209112A1 (en) | Failure detection and response | |
| CN114167470A (en) | Data processing method and device | |
| US9996431B2 (en) | Architecture and apparatus for advanced arbitration in embedded controls | |
| CN111141286A (en) | Unmanned aerial vehicle flight control multi-sensor attitude confidence resolving method | |
| US20220065980A1 (en) | Fault detection, exclusion, isolation, and re-configuration of navigation sensors using an abstraction layer | |
| CN115900796A (en) | Positioning diagnosis method, device, equipment and storage medium | |
| CN113821059A (en) | Multi-rotor unmanned aerial vehicle sensor fault safety flight control system and method |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| GR01 | Patent grant | ||
| GR01 | Patent grant |